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» Intrusion Detection: A Bioinformatics Approach
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SAC
2004
ACM
15 years 5 months ago
Time-frequency feature detection for time-course microarray data
Gene clustering based on microarray data provides useful functional information to the working biologists. Many current gene-clustering algorithms rely on Euclidean-based distance...
Jiawu Feng, Paolo Emilio Barbano, Bud Mishra
BMCBI
2008
123views more  BMCBI 2008»
14 years 11 months ago
Functional module detection by functional flow pattern mining in protein interaction networks
eraction networks. In this abstract, we extend this approach by mining functional flow patterns for the purpose of detecting small-sized modules for specific functions. Methods Our...
Young-Rae Cho, Lei Shi, Aidong Zhang
BMCBI
2006
114views more  BMCBI 2006»
14 years 11 months ago
A high level interface to SCOP and ASTRAL implemented in Python
Background: Benchmarking algorithms in structural bioinformatics often involves the construction of datasets of proteins with given sequence and structural properties. The SCOP da...
James A. Casbon, Gavin E. Crooks, Mansoor A. S. Sa...
90
Voted
CN
2007
91views more  CN 2007»
14 years 11 months ago
Improving the quality of alerts and predicting intruder's next goal with Hidden Colored Petri-Net
Intrusion detection systems (IDS) often provide poor quality alerts, which are insufficient to support rapid identification of ongoing attacks or predict an intruder’s next lik...
Dong Yu, Deborah A. Frincke
ICCV
2003
IEEE
16 years 1 months ago
Feature Selection for Unsupervised and Supervised Inference: the Emergence of Sparsity in a Weighted-based Approach
The problem of selecting a subset of relevant features in a potentially overwhelming quantity of data is classic and found in many branches of science. Examples in computer vision...
Lior Wolf, Amnon Shashua